Implementing Social Tools in Online Learning: Accommodating the native learner or challenging every learner? Lisa F. Rapple SUNY Empire State College
Introduction In 2006 the Pew Internet and American Life Project found that more than 73% of adults in the US use the Internet. Online higher education courses are assuming a growing role in education delivery. Allen and Seaman (2005) found that 2.3 million students attended an online course in 2004 and attendance is growing by 18% each year. A concern for colleges and universities that offer online instruction is how to best serve adult students with a mix of online experiences and aptitudes who aspire to learn via distance. Though it is important that educational transformation occur to improve online education, the question of whether or not the driving force is to accommodate Net Generation learners is yet unanswered.
Digital Natives, Digital Immigrants, and Digital RetireesA review of the literature reveals that the most accepted age range for a "digital native" (the term that this study will use) is anyone born after 1980. These individuals have grown up in a lifestyle that includes personal, digital, and mobile technologies (Oblinger and Oblinger, 2005). Conversely, digital immigrants, born prior to 1980, have experienced an emergence of these technologies during their adult life time. The idea that the Digital Native age group is therefore inherently technology-savvy began to get traction, but is now coming under scrutiny as a growing body of research is now indicating otherwise. Digital Natives, also referred to as “the Net Generation” or “Millenials” make up a growing portion of adult students attending college. Prenski (2001a) coined the term "digital native", and in his studies he concluded that the digital native brings consistent technology skills to the online classroom. Since that time, however, there is a growing body of research that is indicating that this may not be the case. Though this subgroup of adults may have a different submersion into technology, the idea that they have developed a different set of learning needs is not proving to be true. And the use of more “social” tools, emerging technologies as will be defined below, may be a leap for all age groups, including the digital natives. Kennedy, Judd, Churchward, Gray, and Krause (2008) shed light on this possibility in their recent study that surveyed over 2000 students. They examined the students’ access and use of established and emerging technologies. This study of predominantly Digital Natives (n=1973/2120) showed a lack of homogeneity in the Digital Natives’ use of tools, particularly the emerging technologies. Another recent study by Margaryan, Littlejohn, and Vojt (2011), found that university students are using a limited range of technology tools, most of which are established technologies. Many research studies have selected sample frameworks that bias the results. These studies select students enrolled in certain colleges and in certain fields of study that very likely creates a bias. Future studies that broaden the sample frame to include the general population or a broader sample frame of students would produce more accurate results. And would indicate whether the digital native has developed radically new cognitive capacities and learning styles, as Prensky previously has suggested. Learning is a lifelong process that includes students of all ages. The Digital Immigrant spans many decades of age groups. For this reason and for further enlightenment an additional age range is considered for this study. Might digital immigrants have additional impetus to embrace new technologies because of workplace training and job responsibilities that demand integration? Adults who entered retirement age at the time of the technology explosion may have had a different technology experience than the digital immigrant. Adults born after 1930 were of retirement age by 1990. This study will uniquely coin the phrase "Digital Retiree" to explore the use of technology of this age group in contrast to Digital Natives and Digital Immigrants. Technology definitionsThe Kennedy, et al (2008) study of more than 2000 first-year university students was restricted to students born after 1980 (n = 1973; 25.3% of first year students). The Australian digital natives were surveyed about their access, use, and preferences in different types of technology. The findings of Kennedy, et al support previous studies that also found a core set of technology skills. However beyond the core set of technologies there is a diverse range of skills. More importantly those skills do not translate into general information literacy or computer literacy that would add benefit to the pedagogical environment. This study will attempt to show a parallel pattern in the general population of digital natives surveyed in a Pew Study (2010) for social tools and technology use. Kennedy, et al established that there is a core preference of tools and technology that is uniform among digital natives. These include; computers, mobile phones for calling and texting, and Internet use for emailing, instant messaging (IM), and information gathering. These will be referred to in this study as "entrenched technologies".Emerging technologies, though the use and preference among the digital natives is diverse of emerging technologies, it does indicate that they are using these tools that include blogs, mobile digital photography, social networking tools, web conferencing, digital file sharing.Students now use the Internet as their primary source for knowledge acquisition, social networking, and entertainment (Jones, 2002). An important feature of effective adult pedagogy is the collaborative and distributed process of student academic communities. Social networks are an important tool in creating a collaborative community and collaborative workspace for students learning 21st century skills. This study examines age groups of Digital Natives (n = 365 ; 16.2% of adults revealing their age), Digital Immigrants (n= 1685; 74.8% of adults), and Digital Retirees (n = 204; 9.1%) to compare how each group incorporates new technologies into their social activities, and determine if there is a significant difference in frequency or type of technologies used. By examining the data collected in the Pew Social Tools study, it is hoped to determine; whether digital natives are moving beyond entrenched technologies to emerging technologies at a different pace than other age groups, whether each age group uses entrenched technologies (computer, e-mail, cell, text) and emerging technologies (social media, online discussions) at different frequencies, and whether there is a difference in preferences for type of tool, types of use, amount of use. It may then be possible to make inferences on how to better engage all adult age groups using social media in the online classroom.Hypothesis questionDoes the use of Internet social tools vary between the digital native and the digital immigrant? Are there variations in type of tool, purpose for use, and frequency-of-use of social tools between working-age adults and retirement-age adults? Is the Digital Native inherently technology-savvy as compared to Digital Immigrants? Is the digital native more prolific in the use and diversity of emerging technologies? Null hypothesisThe use of emerging technologies is the same for digital natives as it is for all adults regardless of age. There is little difference in the way that digital natives and digital immigrants use Internet social tools; including the type of tool, the reason for using a tool, the frequency of use. There is little impact on the use of social tools, if an adult is of working age or of retirement age. Methodology Population/sample frame PEW Research Center conducted a survey of Americans’ use of the Internet in December of 2010. This report is based on the data that was conducted during that survey. The surveys were administered bay Princeton Survey Research Associates International through telephone interviews. The population sample frame for the survey is all adults in the continental United States who have access to a landline or cellular telephone. The original researchers reported a 95% confidence that the errors attributed to sampling were plus or minus 2.3 percentage points. Sampling Probability sampling (two-stage clustering?) was used for landline survey subjects. Probability selections were in proportion to the number of households in each active block of telephone numbers. Systematic sampling was used for the cellular survey subjects. A list was not used for cellular numbers. Instead 100 blocks of numbers that had no association with landlines were systematically sampled. Bias corrections A two-stage weighting procedure was used to correct for the dual frame sampling so as to avoid bias results. Probability selection adjustment (PSA) was used to correct for the landline probability of accessing several adults in contrast to the cellular phones being personal to one adult. Phone use adjustment (PUA) corrected for the possible overlapping of the sample frames (adults who have a landline and a cell phone). Weighting was also done to balance the sample demographics with the population parameters. A balance was made using the US Census definitions and balancing with the 2000 Census data for demographics. Independent variable The Pew study asked respondents their age. Adults from 18 to 97 were surveyed. The histogram shows a skewness (.041) to the right d/t the fact that the range does not include children. The level of measurement is scale. Of the 2303 respondents 2.1% refused to report their age. The refusal answers were coded with a value of 98 and 99. This can be seen in the first histogram (Figure 1) as a misrepresentation of age. These respondents (n=49) were removed from the age data as seen in the second histogram in Figure 1.
Figure 1Using SPSS the age scale was re-coded into one nominal and two scale variables for age;
Digital natives and Digital Immigrants (nominal)
digital natives, digital immigrants, digital “retirees”, and
age by decade (ages broken into 10 year increments).
To illuminate the exploration of the age data several new variables are created and considered. This exploration helped to focus interest in Digital Natives and Digital Immigrants(DigitalAge), and a unique age range coined “Digital Retiree”(DigitalAgeRetire). A scale variable of ages by decade (DigitalAgeDecade) was also helpful in exploring the data set. Along with the several scale variables that were created from the age data, a dummy variable was made for each age range identified for this investigation.
Figure 2 Dependent variables Current research has explored the use of entrenched technologies and emerging technologies by the digital native and the online student. Current research calls for further inquiry into the use of these technologies by students of all ages. To that end, the survey data was evaluated for questions regarding these two technology groups. Here is a chart synopsis of the questions pertaining to entrenched technologies and emerging technologies: Table 1: |||| Entrenched Technologies
Emerging Technologies
Technology
Q#
Technology
Q #
Use of Internet
18a
Social networks
34e
Visit a website
34c
Social networks
34f
Online discussion
34a
Social networks
ACT87a
Email
34b
Twitter
ACT112a
34d
Twitter
34g
29
Twitter
34h
30
Cell phone & text
34i
18b
23a, b, c, d
23b
23c
Continuous dependent variables for “Entrenched Technologies” (USEENTRENCH) and “Emerging Technologies” (EMERGE) are created using SPSS to re-code. Responses of “don’t know” or “refused” are eliminated. The overall engagement can be seen in Figure 3:
Not engaged Extremely Engaged Figure 3: Overall engagement of adults with entrenched and emerging technologies reveals high engagement with entrenched technologies and no or little engagement with emerging technologies.
Results Pearson’s R correlation for digital age and use of emerging technologies is r(2254) = -.320, p >0.01. Showing a strong inverse correlation. I can’t seem to make a scatterplot!
References Helsper, E.J., and Eynon, R. (2010). Digital natives: where is the evidence? British Educational Research Journal, 36(3), 503 – 520. Doi:10.1080/01411920902989227 Kennedy, G., Judd, T., Churchward, A., Gray, K., & Krause, K.-L. (2008). First year students’ experiences with technology: are they digital natives? Australasian Journal of Educational Technology, 24(1), 108 – 122. Margaryan, A., Littlejohn, A., Vojt, G. (2011). Are Digital natives a myth or reality? University students’ use of digital technologies. Computers & Education. 429 – 440. doi:10.1016/j.compedu.2010.09.004 Nagler, W., & Ebner, M. (June 22 – 26, 2009). Is your university ready for the Ne(x)t Generation?. In Proceedings of 21st world conference on educational multimedia, hypermedia and telecommunications (EDMEDIA) (pp. 4344 – 4351), Honolulu, Hawaii, USA. Oblinger, D., & Oblinger, J. (2005). Is it age or IT: first steps towards understanding the net generation. In D. Oblinger, & J. Oblinger (eds.), Educating the Net Generation (pp. 2.1 – 2.20). Boulder, CO: EDUCAUSE. http://www.educause.edu/educatingthenetgen. Prensky, M. (2001). Digital natives, digital immigrants: do they really think differently? On the Horizon, 9(6), 1 – 6. Social Side of the Internet Survey (2010). Princeton Survey Research Associates International for the Pew Research Center’s Internet and American Life Project. Downloaded 6/21/2011.
Stuff: Level of social activity (Q4a-n, Q7a-n)hours/week of social activity (Q14), impact of internet on social activity of group (Q16), (Q17e-j) General use of Internet (18a)Visit a website (34c)Use of e-mail (18b)(34b)(34d)text(34i)E-mail from home (19a)E-mail from work (19b)Laptop connectivity (22a-b)(MODEMA)Cell phone for social use (23a-d)Social networking tools:Facebook, etc. (ACT87a) (34e-f)Twitter (ACT112a)(34g-h)Entrenched technologies variable: a new continuous variable will be generated from these Yes/No/Don't know/Refused questionscomputer = 18a, 34c, email = 34b, 34d, 29, 30email frequency = 19a, 19b (these two have 6 choice likert scale??)cell phone & text = 34i, 18b, 23a, 23b, 23conline discussion = 34aEmerging technologies variable: a new continuous variable will be generated from these questionsACT87a, 34e, 34f, ACT 112a, 34g, 34h (new continuous variable will be a continuous 0 - 7 scale)Data check:No missing data was found.Eliminate49 of the respondents (2.1% of the data set) refused to give their age, so their data is eliminated pairwise.
Implementing Social Tools in Online Learning: Accommodating the native learner or challenging every learner?
Lisa F. Rapple
SUNY Empire State College
Introduction
In 2006 the Pew Internet and American Life Project found that more than 73% of adults in the US use the Internet. Online higher education courses are assuming a growing role in education delivery. Allen and Seaman (2005) found that 2.3 million students attended an online course in 2004 and attendance is growing by 18% each year. A concern for colleges and universities that offer online instruction is how to best serve adult students with a mix of online experiences and aptitudes who aspire to learn via distance. Though it is important that educational transformation occur to improve online education, the question of whether or not the driving force is to accommodate Net Generation learners is yet unanswered.
Digital Natives, Digital Immigrants, and Digital RetireesA review of the literature reveals that the most accepted age range for a "digital native" (the term that this study will use) is anyone born after 1980. These individuals have grown up in a lifestyle that includes personal, digital, and mobile technologies (Oblinger and Oblinger, 2005). Conversely, digital immigrants, born prior to 1980, have experienced an emergence of these technologies during their adult life time. The idea that the Digital Native age group is therefore inherently technology-savvy began to get traction, but is now coming under scrutiny as a growing body of research is now indicating otherwise. Digital Natives, also referred to as “the Net Generation” or “Millenials” make up a growing portion of adult students attending college. Prenski (2001a) coined the term "digital native", and in his studies he concluded that the digital native brings consistent technology skills to the online classroom. Since that time, however, there is a growing body of research that is indicating that this may not be the case. Though this subgroup of adults may have a different submersion into technology, the idea that they have developed a different set of learning needs is not proving to be true. And the use of more “social” tools, emerging technologies as will be defined below, may be a leap for all age groups, including the digital natives. Kennedy, Judd, Churchward, Gray, and Krause (2008) shed light on this possibility in their recent study that surveyed over 2000 students. They examined the students’ access and use of established and emerging technologies. This study of predominantly Digital Natives (n=1973/2120) showed a lack of homogeneity in the Digital Natives’ use of tools, particularly the emerging technologies. Another recent study by Margaryan, Littlejohn, and Vojt (2011), found that university students are using a limited range of technology tools, most of which are established technologies.
Many research studies have selected sample frameworks that bias the results. These studies select students enrolled in certain colleges and in certain fields of study that very likely creates a bias. Future studies that broaden the sample frame to include the general population or a broader sample frame of students would produce more accurate results. And would indicate whether the digital native has developed radically new cognitive capacities and learning styles, as Prensky previously has suggested.
Learning is a lifelong process that includes students of all ages. The Digital Immigrant spans many decades of age groups. For this reason and for further enlightenment an additional age range is considered for this study. Might digital immigrants have additional impetus to embrace new technologies because of workplace training and job responsibilities that demand integration? Adults who entered retirement age at the time of the technology explosion may have had a different technology experience than the digital immigrant. Adults born after 1930 were of retirement age by 1990. This study will uniquely coin the phrase "Digital Retiree" to explore the use of technology of this age group in contrast to Digital Natives and Digital Immigrants.
Technology definitionsThe Kennedy, et al (2008) study of more than 2000 first-year university students was restricted to students born after 1980 (n = 1973; 25.3% of first year students). The Australian digital natives were surveyed about their access, use, and preferences in different types of technology. The findings of Kennedy, et al support previous studies that also found a core set of technology skills. However beyond the core set of technologies there is a diverse range of skills. More importantly those skills do not translate into general information literacy or computer literacy that would add benefit to the pedagogical environment. This study will attempt to show a parallel pattern in the general population of digital natives surveyed in a Pew Study (2010) for social tools and technology use. Kennedy, et al established that there is a core preference of tools and technology that is uniform among digital natives. These include; computers, mobile phones for calling and texting, and Internet use for emailing, instant messaging (IM), and information gathering. These will be referred to in this study as "entrenched technologies".Emerging technologies, though the use and preference among the digital natives is diverse of emerging technologies, it does indicate that they are using these tools that include blogs, mobile digital photography, social networking tools, web conferencing, digital file sharing.Students now use the Internet as their primary source for knowledge acquisition, social networking, and entertainment (Jones, 2002). An important feature of effective adult pedagogy is the collaborative and distributed process of student academic communities. Social networks are an important tool in creating a collaborative community and collaborative workspace for students learning 21st century skills.
This study examines age groups of Digital Natives (n = 365 ; 16.2% of adults revealing their age), Digital Immigrants (n= 1685; 74.8% of adults), and Digital Retirees (n = 204; 9.1%) to compare how each group incorporates new technologies into their social activities, and determine if there is a significant difference in frequency or type of technologies used. By examining the data collected in the Pew Social Tools study, it is hoped to determine;
whether digital natives are moving beyond entrenched technologies to emerging technologies at a different pace than other age groups, whether each age group uses entrenched technologies (computer, e-mail, cell, text) and emerging technologies (social media, online discussions) at different frequencies, and whether there is a difference in preferences for type of tool, types of use, amount of use. It may then be possible to make inferences on how to better engage all adult age groups using social media in the online classroom.Hypothesis questionDoes the use of Internet social tools vary between the digital native and the digital immigrant? Are there variations in type of tool, purpose for use, and frequency-of-use of social tools between working-age adults and retirement-age adults? Is the Digital Native inherently technology-savvy as compared to Digital Immigrants? Is the digital native more prolific in the use and diversity of emerging technologies?
Null hypothesisThe use of emerging technologies is the same for digital natives as it is for all adults regardless of age.
There is little difference in the way that digital natives and digital immigrants use Internet social tools; including the type of tool, the reason for using a tool, the frequency of use. There is little impact on the use of social tools, if an adult is of working age or of retirement age.
Methodology
Population/sample frame
PEW Research Center conducted a survey of Americans’ use of the Internet in December of 2010. This report is based on the data that was conducted during that survey. The surveys were administered bay Princeton Survey Research Associates International through telephone interviews. The population sample frame for the survey is all adults in the continental United States who have access to a landline or cellular telephone. The original researchers reported a 95% confidence that the errors attributed to sampling were plus or minus 2.3 percentage points.
Sampling
Probability sampling (two-stage clustering?) was used for landline survey subjects. Probability selections were in proportion to the number of households in each active block of telephone numbers. Systematic sampling was used for the cellular survey subjects. A list was not used for cellular numbers. Instead 100 blocks of numbers that had no association with landlines were systematically sampled.
Bias corrections
A two-stage weighting procedure was used to correct for the dual frame sampling so as to avoid bias results. Probability selection adjustment (PSA) was used to correct for the landline probability of accessing several adults in contrast to the cellular phones being personal to one adult. Phone use adjustment (PUA) corrected for the possible overlapping of the sample frames (adults who have a landline and a cell phone).
Weighting was also done to balance the sample demographics with the population parameters. A balance was made using the US Census definitions and balancing with the 2000 Census data for demographics.
Independent variable
The Pew study asked respondents their age. Adults from 18 to 97 were surveyed. The histogram shows a skewness (.041) to the right d/t the fact that the range does not include children. The level of measurement is scale. Of the 2303 respondents 2.1% refused to report their age. The refusal answers were coded with a value of 98 and 99. This can be seen in the first histogram (Figure 1) as a misrepresentation of age. These respondents (n=49) were removed from the age data as seen in the second histogram in Figure 1.
Figure 1Using SPSS the age scale was re-coded into one nominal and two scale variables for age;
- Digital natives and Digital Immigrants (nominal)
- digital natives, digital immigrants, digital “retirees”, and
- age by decade (ages broken into 10 year increments).
To illuminate the exploration of the age data several new variables are created and considered. This exploration helped to focus interest in Digital Natives and Digital Immigrants(DigitalAge), and a unique age range coined “Digital Retiree”(DigitalAgeRetire). A scale variable of ages by decade (DigitalAgeDecade) was also helpful in exploring the data set. Along with the several scale variables that were created from the age data, a dummy variable was made for each age range identified for this investigation.Figure 2
Dependent variables
Current research has explored the use of entrenched technologies and emerging technologies by the digital native and the online student. Current research calls for further inquiry into the use of these technologies by students of all ages. To that end, the survey data was evaluated for questions regarding these two technology groups. Here is a chart synopsis of the questions pertaining to entrenched technologies and emerging technologies:
Table 1:
|||| Entrenched Technologies
Continuous dependent variables for “Entrenched Technologies” (USEENTRENCH) and “Emerging Technologies” (EMERGE) are created using SPSS to re-code. Responses of “don’t know” or “refused” are eliminated. The overall engagement can be seen in Figure 3:
Not engaged Extremely Engaged
Figure 3: Overall engagement of adults with entrenched and emerging technologies reveals high engagement with entrenched technologies and no or little engagement with emerging technologies.
Results
Pearson’s R correlation for digital age and use of emerging technologies is r(2254) = -.320, p >0.01. Showing a strong inverse correlation.
I can’t seem to make a scatterplot!
References
Helsper, E.J., and Eynon, R. (2010). Digital natives: where is the evidence? British Educational Research Journal, 36(3), 503 – 520. Doi:10.1080/01411920902989227
Kennedy, G., Judd, T., Churchward, A., Gray, K., & Krause, K.-L. (2008). First year students’ experiences with technology: are they digital natives? Australasian Journal of Educational Technology, 24(1), 108 – 122.
Margaryan, A., Littlejohn, A., Vojt, G. (2011). Are Digital natives a myth or reality? University students’ use of digital technologies. Computers & Education. 429 – 440. doi:10.1016/j.compedu.2010.09.004
Nagler, W., & Ebner, M. (June 22 – 26, 2009). Is your university ready for the Ne(x)t Generation?. In Proceedings of 21st world conference on educational multimedia, hypermedia and telecommunications (EDMEDIA) (pp. 4344 – 4351), Honolulu, Hawaii, USA.
Oblinger, D., & Oblinger, J. (2005). Is it age or IT: first steps towards understanding the net generation. In D. Oblinger, & J. Oblinger (eds.), Educating the Net Generation (pp. 2.1 – 2.20). Boulder, CO: EDUCAUSE. http://www.educause.edu/educatingthenetgen.
Prensky, M. (2001). Digital natives, digital immigrants: do they really think differently? On the Horizon, 9(6), 1 – 6.
Social Side of the Internet Survey (2010). Princeton Survey Research Associates International for the Pew Research Center’s Internet and American Life Project. Downloaded 6/21/2011.
Stuff:
Level of social activity (Q4a-n, Q7a-n)hours/week of social activity (Q14),
impact of internet on social activity of group (Q16), (Q17e-j)
General use of Internet (18a)Visit a website (34c)Use of e-mail (18b)(34b)(34d)text(34i)E-mail from home (19a)E-mail from work (19b)Laptop connectivity (22a-b)(MODEMA)Cell phone for social use (23a-d)Social networking tools:Facebook, etc. (ACT87a) (34e-f)Twitter (ACT112a)(34g-h)Entrenched technologies variable: a new continuous variable will be generated from these Yes/No/Don't know/Refused questionscomputer = 18a, 34c, email = 34b, 34d, 29, 30email frequency = 19a, 19b (these two have 6 choice likert scale??)cell phone & text = 34i, 18b, 23a, 23b, 23conline discussion = 34aEmerging technologies variable: a new continuous variable will be generated from these questionsACT87a, 34e, 34f, ACT 112a, 34g, 34h (new continuous variable will be a continuous 0 - 7 scale)Data check:No missing data was found.Eliminate49 of the respondents (2.1% of the data set) refused to give their age, so their data is eliminated pairwise.